Founding Lead of Agentic Analytics (AI)

Location: Hybrid in the United States or Canada; listed locations include Montreal, New York, Ottawa, San Francisco, and Toronto.

Base salary: USA California, New York, and Washington $270,000–$325,000; USA other states $250,000–$290,000; Canada CA$350,000–CA$410,000. Equity is offered.

Company

Cohere is a security-first enterprise AI company building foundation AI models and end-to-end products for real-world business problems.

What you will do

• Own the architecture for converting business questions into governed queries and verifiable answers with approved definitions, joins, permissions, and evidence.
• Build and operate production services, agent-facing data tools, context retrieval, analytics skills, and APIs integrated with Slack, North, IDEs, and other agents.
• Develop evaluation harnesses, ground-truth question sets, scoring, abstention metrics, error taxonomies, and regression tests.
• Engineer the context layer using metric definitions, approved joins, documentation, glossaries, and worked examples.
• Roll out the system across marketing, revenue, finance, product, and other domains, measuring adoption, accuracy, turnaround, and correction effort.
• Hire and lead the founding team while partnering with data platform, model evaluation, security, and domain owners.

Requirements

• 10+ years building and operating production analytics or software systems, including technical leadership of a team or systems spanning teams.
• Experience shipping LLM agents to production, including tool use, MCP or similar, retrieval, context engineering, guardrails, and observability.
• Hands-on experience building natural-language or agentic analytics such as text-to-SQL, analytics agents, or question answering over a semantic layer for real users.
• Depth in evaluating LLM systems through golden sets, result-level comparison, abstention metrics, error taxonomies, and CI regression testing.
• Strong Python and SQL skills plus experience designing and operating production services and APIs on a major cloud.
• Experience with cloud warehouses such as BigQuery or Snowflake, dbt, and semantic layers such as MetricFlow, LookML, or Cube.
• Experience building identity-aware agent access where queries use the asking user's permissions and leave an audit trail.
• Experience hiring and developing engineers; ability to operate in ambiguity, lead through partners, and write design documents and evaluation reports.
• Genuine interest in AI research and hands-on technical work.

Nice to have

• Experience with Google Cloud.

Culture & Benefits

• Remote-friendly hybrid environment with offices and co-working support for employees not near an office.
• Full health and dental benefits, mental health budget, RRSP matching, 401K, and pension scheme.
• Six weeks of paid vacation, parental leave top-up for up to six months, and annual enrichment benefits.
• Education and learning stipend, home office stipend, lunch support, and office travel budget.
• Annual company offsite and opportunities to work with teams across international offices.

Hiring process

• Applicants may be screened and assessed using AI-enabled tools.
• Accommodation requests can be submitted through the provided accommodations request form.